Uber · 8 hours ago
Senior Staff Machine Learning Engineer - Driver Pricing & Marketplace Optimization
San Francisco, CA
Full-time
Onsite
Senior Level, Lead/Staff
$257K/yr - $286K/yr
10+ years expUber is seeking an exceptional Senior Staff ML Engineer to lead breakthrough ML innovation in their Driver Pricing organization. In this high-impact role, you'll architect and build next-generation ML systems that optimize marketplace efficiency and driver earnings for millions of drivers globally.
LogisticsMobile AppsRide SharingSoftwareTransportation
Responsibilities
Lead the design and implementation of advanced ML systems for dynamic pricing algorithms serving millions of drivers across 70+ countries around the world
Architect real-time ML infrastructure handling 1M+ pricing decisions per second with sub-50ms latency requirements
Drive breakthrough research in causal ML, reinforcement learning, algorithmic game theory, and multi-objective optimization for marketplace optimization with strategic agents
Own end-to-end ML model lifecycle from research through production deployment and continuous optimization
Build scalable ML architecture and feature management systems supporting Driver Pricing and broader Marketplace teams
Design experimentation frameworks enabling rapid testing of pricing algorithms using A/B, Switchback, Synthetic Control, and other experimental methodologies
Establish ML engineering best practices, monitoring, and operational excellence across the organization
Create platform abstractions that enable other ML engineers to iterate faster on pricing algorithms
Partner with Product, Operations, and Earner Experience teams to translate complex business requirements into ML solutions
Collaborate with Marketplace Engineering and Science teams to productionize cutting-edge ML research
Work with Platform Engineering teams to ensure ML systems meet reliability and performance standards
Influence technical roadmaps across multiple teams through technical leadership and strategic thinking
Mentor and grow senior ML engineers, establishing technical standards and engineering culture
Lead technical discussions and architecture reviews for complex ML systems
Drive knowledge sharing and technical excellence across the Driver Pricing engineering organization
Qualification
Required
PhD in Computer Science, Machine Learning, Operations Research, or related quantitative field OR Master's degree with 12+ years of industry experience
10+ years of experience building and deploying ML models in large-scale production environments
Expert-level proficiency in modern ML frameworks (TensorFlow, PyTorch, JAX) and distributed computing platforms (Spark, Ray)
Deep expertise across multiple areas including: Deep Learning, Causal Inference, Reinforcement Learning, Multi-objective Optimization, Algorithmic Game Theory, and Large-scale Ads Ranking/Auction Systems
Proven track record of leading complex ML projects from research through production with significant measurable business impact
Strong programming skills in Python, Java, or Go with experience building production ML systems
Experience with feature engineering, model serving, and ML infrastructure at scale (handling millions of predictions per second)
Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives
Advanced Deep Learning and Neural Network architectures
Scalable ML architecture and distributed model training
Feature engineering and real-time feature serving
ML model deployment, monitoring, and lifecycle management
Statistical analysis and experimental design for ML systems
Causal Machine Learning and causal inference methodologies
Reinforcement Learning and Multi-Armed Bandits
Multi-objective optimization and Pareto efficiency
Algorithmic Game Theory for strategic agent modeling
Preferred
Marketplace or two-sided platform ML experience with understanding of supply-demand dynamics and pricing mechanisms
Publications or patents in applied machine learning, particularly in areas relevant to optimization, pricing, or marketplace dynamics
Experience with causal inference methodologies and their application to business problems with network effects
Reinforcement learning experience in production environments with long-term optimization and strategic agent considerations
Technical leadership experience including mentoring senior engineers and driving cross-team technical initiatives
Experience with real-time ML systems requiring low-latency inference and high-throughput model serving
Background in economics, operations research, or related quantitative disciplines with application to marketplace problems
Experience with Ads ranking and auction systems with strategic bidding agents and real-time optimization
Benefits
You will also be eligible for various benefits.
Company
Uber
Uber develops, markets, and operates a ride-sharing mobile application that allows consumers to submit a trip request.
10001+ employees
H1B Sponsorship
Uber has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (830)
2024 (796)
2023 (684)
2022 (954)
2021 (750)
2020 (638)
Funding
Current Stage
Public CompanyTotal Funding
$35.56BKey Investors
William AckmanPayPalToyota Motor
2025-09-08Post Ipo Debt· $2.25B
2025-05-13Post Ipo Debt· $1B
2025-01-01Post Ipo Equity· $2.3B
Leadership Team
Dara Khosrowshahi
CEO
Prashanth Mahendra -Rajah
Chief Financial Officer
Recent News
Foundation Capital
2025-12-31
2025-12-31
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